DeepSeek AI has launched the Fire-Flyer File System (3FS), a distributed file system designed for AI training and inference workloads. 3FS addresses the growing data and computational demands of AI by offering a high-throughput, scalable storage solution. It combines the capabilities of thousands of SSDs with numerous storage nodes, bypassing traditional data locality limitations. Key features include Chain Replication with Apportioned Queries (CRAQ) for strong consistency and stateless metadata services supported by a transactional key-value store. Performance benchmarks show 3FS achieving a read throughput of 6.6 TiB/s and efficient data sorting, along with a high KVCache read throughput of 40 GiB/s for inference tasks.
DeepSeek AI Releases Fire-Flyer File System (3FS): A High-Performance Distributed File System Designed to Address the Challenges of AI Training and Inference Workload
Key Takeaways
- DeepSeek AI has launched the Fire-Flyer File System (3FS), a distributed file system designed for AI training and inference workloads.
- 3FS addresses the growing data and computational demands of AI by offering a high-throughput, scalable storage solution.
- It combines the capabilities of thousands of SSDs with numerous storage nodes, bypassing traditional data locality limitations.
- Key features include Chain Replication with Apportioned Queries (CRAQ) for strong consistency and stateless metadata services supported by a transactional key-value store.
- Performance benchmarks show 3FS achieving a read throughput of 6.6 TiB/s and efficient data sorting, along with a high KVCache read throughput of 40 GiB/s for inference tasks.
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